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Imposing Moment Restrictions from Auxiliary Data by Weighting

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  • Guido W. Imbens
  • Judith K. Hellerstein

Abstract

In this paper we analyze estimation of coefficients in regression models under moment restrictions where the moment restrictions are derived from auxiliary data. Our approach is similar to those that have been used in statistics for analyzing contingency tables with known marginals. These methods are useful in cases where data from a small, potentially non-representative data set can be supplemented with auxiliary information from another data set which may be larger and/or more representative of the target population. The moment restrictions yield weights for each observation that can subsequently be used in weighted regression analysis. We discuss the interpretation of these weights both under the assumption that the target population and the sampled population are the same, as well as under the assumption that these popula- tions differ. We present an application based on omitted ability bias in estimation of wage regressions. The National Longitudinal Survey Young Men's Cohort (NLS), as well as containing information for each observation on earn- ings, education and experience, records data on two test scores that may be considered proxies for ability. The NLS is a small data set, however, with a high attrition rate. We investigate how to mitigate these problems in the NLS by forming moments from the joint distribution of education, experience and earnings in the 1% sample of the 1980 U.S. Census and using these moments to construct weights for weighted regression analysis of the NLS. We analyze the impacts of our weighted regression techniques on the estimated coefficients and standard errors on returns to education and experience in the NLS control- ling for ability, with and without assuming that the NLS and the Census samples are random samples from the same population.

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Bibliographic Info

Paper provided by National Bureau of Economic Research, Inc in its series NBER Technical Working Papers with number 0202.

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Date of creation: Aug 1996
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Publication status: published as Review of Economics and Statistics (1999).
Handle: RePEc:nbr:nberte:0202

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  1. Blackburn, McKinley & Neumark, David, 1992. "Unobserved Ability, Efficiency Wages, and Interindustry Wage Differentials," The Quarterly Journal of Economics, MIT Press, vol. 107(4), pages 1421-36, November.
  2. Imbens, G.W., 1991. "An Efficient Method Of Moments Estimator For Discrete Choice Models With Choice-Based Sampling," Harvard Institute of Economic Research Working Papers 1546, Harvard - Institute of Economic Research.
  3. Guido W. Imbens & Phillip Johnson & Richard H. Spady, 1995. "Information Theoretic Approaches to Inference in Moment Condition Models," NBER Technical Working Papers 0186, National Bureau of Economic Research, Inc.
  4. Hausman, Jerry A & Wise, David A, 1979. "Attrition Bias in Experimental and Panel Data: The Gary Income Maintenance Experiment," Econometrica, Econometric Society, vol. 47(2), pages 455-73, March.
  5. Imbens, G.W. & Lancaster, T., 1991. "Combining Micro and Macro Data in Microeconometric Models," Harvard Institute of Economic Research Working Papers 1578, Harvard - Institute of Economic Research.
  6. Newey, Whitney K. & McFadden, Daniel, 1986. "Large sample estimation and hypothesis testing," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 36, pages 2111-2245 Elsevier.
  7. Griliches, Zvi, 1977. "Estimating the Returns to Schooling: Some Econometric Problems," Econometrica, Econometric Society, vol. 45(1), pages 1-22, January.
  8. Keane, Michael & Moffitt, Robert & Runkle, David, 1988. "Real Wages over the Business Cycle: Estimating the Impact of Heterogeneity with Micro Data," Journal of Political Economy, University of Chicago Press, vol. 96(6), pages 1232-66, December.
  9. Imbens, G., 1993. "A New Approach to Generalized Method on Moments Estimation," Harvard Institute of Economic Research Working Papers 1633, Harvard - Institute of Economic Research.
  10. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-38, May.
  11. Ridder, Geert, 1992. "An empirical evaluation of some models for non-random attrition in panel data," Structural Change and Economic Dynamics, Elsevier, vol. 3(2), pages 337-355, December.
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